Changeset 4401 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3

Timestamp:

09/15/10 21:11:11 (14 years ago)

Author:

gkronber

Message:

Added model and solution classes for time series prognosis and added views for time series prognosis solutions. #1142

Location:

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3

Files:

• HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis-3.3.csproj (modified) (1 diff)
• Symbolic/Analyzer/ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer.cs (modified) (4 diffs)
• Symbolic/Evaluators/SymbolicTimeSeriesPrognosisNormalizedMseEvaluator.cs (modified) (1 diff)
• Symbolic/Evaluators/SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator.cs (modified) (1 diff)
• Symbolic/SymbolicTimeSeriesPrognosisModel.cs (added)
• Symbolic/SymbolicTimeSeriesPrognosisSolution.cs (added)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis-3.3.csproj

@@ -108 +108 @@
     <Compile Include="HeuristicLabProblemsDataAnalysisMultiVariateTimeSeriesPrognosisPlugin.cs" />
     <Compile Include="Symbolic\Analyzer\ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer.cs" />
+    <Compile Include="Symbolic\SymbolicTimeSeriesPrognosisSolution.cs" />
+    <Compile Include="Symbolic\SymbolicTimeSeriesPrognosisModel.cs" />
     <Compile Include="Symbolic\Evaluators\SymbolicTimeSeriesPrognosisNormalizedMseEvaluator.cs" />
     <Compile Include="Symbolic\Evaluators\SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator.cs" />

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Analyzer/ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer.cs

@@ -152 +152 @@
       get { return (IValueLookupParameter<IntValue>)Parameters[PredictionHorizonParameterName]; }
     }
-    public ILookupParameter<SymbolicExpressionTree> BestSolutionParameter {
-      get { return (ILookupParameter<SymbolicExpressionTree>)Parameters[BestSolutionParameterName]; }
+    public ILookupParameter<SymbolicTimeSeriesPrognosisSolution> BestSolutionParameter {
+      get { return (ILookupParameter<SymbolicTimeSeriesPrognosisSolution>)Parameters[BestSolutionParameterName]; }
     }
     public ILookupParameter<IntValue> GenerationsParameter {
@@ -239 +239 @@
       Parameters.Add(new ValueLookupParameter<DoubleArray>(UpperEstimationLimitParameterName, "The upper estimation limit that was set for the evaluation of the symbolic expression trees."));
       Parameters.Add(new ValueLookupParameter<DoubleArray>(LowerEstimationLimitParameterName, "The lower estimation limit that was set for the evaluation of the symbolic expression trees."));
-      Parameters.Add(new LookupParameter<SymbolicExpressionTree>(BestSolutionParameterName, "The best symbolic time series prognosis solution."));
+      Parameters.Add(new LookupParameter<SymbolicTimeSeriesPrognosisSolution>(BestSolutionParameterName, "The best symbolic time series prognosis solution."));
       Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "The number of generations calculated so far."));
       Parameters.Add(new LookupParameter<DoubleValue>(BestSolutionQualityParameterName, "The quality of the best symbolic regression solution."));
@@ -274 +274 @@
       int validationEnd = ValidationSamplesEnd.Value;
       int rowCount = (int)Math.Ceiling((validationEnd - validationStart) * RelativeNumberOfEvaluatedSamples.Value);
-      IEnumerable<int> rows = RandomEnumerable.SampleRandomNumbers((uint)Random.Next(), validationStart, validationEnd, rowCount);
+      IEnumerable<int> rows = RandomEnumerable.SampleRandomNumbers(Random.Next(), validationStart, validationEnd, rowCount);
       double bestValidationNmse = double.MaxValue;
       SymbolicExpressionTree bestTree = null;
@@ -291 +291 @@
 
       if (BestSolutionQualityParameter.ActualValue == null || BestSolutionQualityParameter.ActualValue.Value > bestValidationNmse) {
-        var solution = bestTree;
-        //solution.Name = BestSolutionParameterName;
-        //solution.Description = "Best solution on validation partition found over the whole run.";
+        var model = new SymbolicTimeSeriesPrognosisModel((ISymbolicTimeSeriesExpressionInterpreter)SymbolicExpressionTreeInterpreter.Clone(), bestTree);
+        model.Name = "Time series prognosis model";
+        model.Description = "Best solution on validation partition found over the whole run.";
+
+        var solution = new SymbolicTimeSeriesPrognosisSolution(ProblemData, model, PredictionHorizon.Value);
+        solution.Name = BestSolutionParameterName;
+        solution.Description = "Best solution on validation partition found over the whole run.";
 
         BestSolutionParameter.ActualValue = solution;

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Evaluators/SymbolicTimeSeriesPrognosisNormalizedMseEvaluator.cs

@@ -149 +149 @@
       string conditionVariableName = ConditionVariableName == null ? null : ConditionVariableName.Value;
       int nRows = (int)Math.Ceiling((SamplesEnd.Value - SamplesStart.Value) * RelativeNumberOfEvaluatedSamples.Value);
-      IEnumerable<int> rows = RandomEnumerable.SampleRandomNumbers((uint)Random.Next(), SamplesStart.Value, SamplesEnd.Value, nRows);
+      IEnumerable<int> rows = RandomEnumerable.SampleRandomNumbers(Random.Next(), SamplesStart.Value, SamplesEnd.Value, nRows);
 
       quality = Evaluate(TimeSeriesPrognosisModel, ProblemData, TimeSeriesExpressionInterpreter,

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Evaluators/SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator.cs

@@ -162 +162 @@
       int nRows = (int)Math.Ceiling((SamplesEnd.Value - SamplesStart.Value) * RelativeNumberOfEvaluatedSamples.Value);
 
-      IEnumerable<int> rows = RandomEnumerable.SampleRandomNumbers((uint)Random.Next(), SamplesStart.Value, SamplesEnd.Value, nRows);
+      IEnumerable<int> rows = RandomEnumerable.SampleRandomNumbers(Random.Next(), SamplesStart.Value, SamplesEnd.Value, nRows);
       CalculateScalingParameters(TimeSeriesPrognosisModel, ProblemData, TimeSeriesExpressionInterpreter,
         conditionVariableName, rows,